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The minimax-optimal exponent describes the best error convergence rate that any estimation method can achieve across all possible data-generating distributions and in the worst case.
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10/19/2026
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UnverifiedAssuming the data follows a Gaussian distribution, maximizing the likelihood is equivalent to minimizing the mean squared error.79% similarUnverifiedThe researchers proposed Minimax RR-ICM, which optimizes over the worst case over probability distributions on the sphere rather than averaging over directions.71% similarUnverifiedThe algorithm employs variance-reduced estimation of the Bellman optimality operator locally at each agent.70% similarUnverifiedAverage accuracy masks distributional skew; a judge that gets all easy cases right and is overconfident on hard cases can post a high average score while failing at critical points.69% similarUnverifiedCVaR_α measures the average loss of a random variable in the worst (1-α) fraction of cases; as α→1 it degenerates to the expected value, and as α→0 it approaches the worst-case cost.69% similar
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